directory-management

directory-management is a skill for Claude Code from awslabs/agent-plugins. It costs 62 tokens per session (379 once invoked), scanned A, original, Apache-2.0.

A project-folder setup and organization skill for keeping plans, scripts, notebooks, manifests, and agent notes in predictable locations. A manifest is a machine-readable record of project outputs.

In plain words
What is it for?
Use it to choose a project name, create its folder structure, resume projects containing a PLAN.md file, and organize generated artifacts.
Why use it?
It prevents project files from being scattered or assigned to the wrong project, especially when starting work or returning to an existing plan.

Skill for Claude Code ✓ vendor

Written for Claude Code: shipped in a Claude Code plugin.

Part of the sagemaker-ai plugin — 19 skills shipped together

Good fit Use it to choose a project name, create its folder structure, resume projects containing a PLAN.md file, and organize generated artifacts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/awslabs/agent-plugins/directory-management
About the project

awslabs/agent-plugins is a collection of plugins, skills, instructions, an MCP server, a hook, and a setting that guide AI coding agents in architecting, deploying, and operating software on Amazon Web Services. It is for developers using coding agents such as Claude Code, Codex, and Cursor with AWS projects. The catalogue entries are the repository's own agent workflows and supporting components.

awslabs/agent-plugins · 924 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add awslabs/agent-plugins --skill directory-management
Clone the repo
git clone --depth 1 https://github.com/awslabs/agent-plugins

Made for: Claude Code.

Or install sagemaker-ai, the plugin that ships this one along with the rest of its 19 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for directory-management

README.md
[![agentmods](https://agentmods.dev/badge/skills/awslabs/agent-plugins/directory-management/github.svg)](https://agentmods.dev/skills/awslabs/agent-plugins/directory-management)
Your own site
<a href="https://agentmods.dev/skills/awslabs/agent-plugins/directory-management"><img src="https://agentmods.dev/badge/skills/awslabs/agent-plugins/directory-management/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for directory-management

Your own site · 80×15
<a href="https://agentmods.dev/skills/awslabs/agent-plugins/directory-management"><img src="https://agentmods.dev/badge/skills/awslabs/agent-plugins/directory-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 379 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00062 $0.00379
Opus 5.5 $0.00025 $0.00152
Sonnet 5.5 $0.00012 $0.00076
Haiku 4.5 $0.00006 $0.00038

Measured 1mo ago against content hash 19c160fb3f80, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

directory-management scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/sagemaker-ai/skills/directory-management/SKILL.md · 38 lines

What it actually says

Directory Management

Project Setup

Before any work begins, resolve the project name:

  1. If the project name is already known from conversation context, use it.
  2. Otherwise, scan for existing */PLAN.md files in the current directory. If found, ask the user if they are resuming an existing project and load that PLAN.md into context.
  3. If no existing projects are found, recommend a ≤64-char lowercase slug based on what you know from the conversation (only [a-z0-9-]), or ask directly if there isn't enough context. Present the recommended name and wait for user confirmation.

Once project name is resolved:

  1. Create and/or use the <experiment-name>/ directory using the confirmed name for storing all the artifacts

Directory Structure

When working with the agent, all generated files are organized under an project directory.

<project-name>/
├── specs/  
│   ├── PLAN.md             # Your customization plan
├── scripts/                # Generated Python scripts
│   ├── <project-name>_transform_fn.py
├── notebooks/              # Generated Jupyter notebooks
│   ├── <project-name>.ipynb
├── manifests/              # Machine-readable outputs (JSON)
└── agent_memory/           # Session persistence (git-ignored)
    └── session-notes.md    # Progress, artifacts, next steps
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 38 lines · 62 tokens per session scan A 19c160fb3f80

Subscribe to this mod's changes

directory-management is a skill published in the GitHub repository awslabs/agent-plugins (924 stars, last pushed 6d ago), licensed Apache-2.0. It adds 62 tokens to every session and 379 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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